Lead the design, planning, estimation, and coordination of AI/ML initiatives across multiple releases, including information extraction, model development, data pipelines, and deployment.
Take ownership of the entire lifecycle of AI/ML systems, from experimentation to production, ensuring timely and high-quality delivery.
Partner with Product and Engineering teams to integrate AI/ML capabilities into company-wide projects, addressing cross-functional challenges.
Collaborate with Product, Engineering, DevOps, and other teams to ensure seamless data flow, model deployment, and system integration.
Provide strategic technical guidance on AI/ML frameworks, tools, and best practices that align with the company’s goals.
Research and propose advanced machine learning techniques and cloud-native AI services, including LLMs, agentic workflows, and Amazon Bedrock, to enhance our capabilities.
Foster a collaborative environment by communicating effectively across technical and non-technical teams.
Mentor and guide team members through agentic coding practices, code reviews, technical coaching, and knowledge sharing, building a culture of continuous learning.
Proactively identify challenges in AI/ML workflows and propose innovative, scalable solutions.
Drive initiatives to improve model accuracy, scalability, and reliability while adhering to privacy, security, and compliance standards.
Ensure comprehensive documentation of models, algorithms, and system architecture to support team-wide knowledge sharing.
Requirements
7+ years of experience in AI/ML engineering, including building, deploying and maintaining machine learning models in production environments.
3+ years of technical leadership experience, with a track record of guiding teams through complex AI/ML projects.
Expert proficiency in programming languages such as Python, Java or Rust, with a focus on data engineering/science, information extraction, machine learning, evaluation frameworks, agentic AI and LLMOps workflows.
Deep understanding of AI/ML systems architecture, including experience with agentic AI frameworks and orchestration patterns, distributed systems and large-scale data pipelines.
Strong expertise in deploying and managing AI/ML models in cloud environments, with hands-on experience using AWS services such as Amazon Bedrock, SageMaker, and related tools, or alternatives in GCP (Vertex AI) or Azure (AI Studio) cloud.
In-depth knowledge of machine learning algorithms and frameworks, including experience with LLMs, AI agentic patterns, and fine-tuning pre-trained models.
Experience with microservices architecture and CI/CD pipelines / MLOps for AI/ML model deployment, ensuring scalability, reusability, and testability.
Experience with agentic AI coding and orchestration tools for software engineering, such as Claude Code, Codex, or similar.
Proven ability to mentor and guide engineers, fostering growth and technical excellence without formal direct reporting relationships.
Strong collaboration skills, working cross-functionally with Engineering, DevOps, and Product teams to deliver impactful AI/ML solutions.
Experience with Agile/Scrum methodologies, effectively managing sprints and delivering iterative improvements.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.